workaround for sort ambiguity in cat_features (#105)

* fix sort ambiguity issue with empty tuple

* bump version

Project.toml

@@ -1,7 +1,7 @@
 name = "GraphNeuralNetworks"
 uuid = "cffab07f-9bc2-4db1-8861-388f63bf7694"
 authors = ["Carlo Lucibello and contributors"]
-version = "0.3.8"
+version = "0.3.9"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
@@ -46,9 +46,11 @@ julia = "1.6"
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
+InlineStrings = "842dd82b-1e85-43dc-bf29-5d0ee9dffc48"
 MLDatasets = "eb30cadb-4394-5ae3-aed4-317e484a6458"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["Test", "Adapt", "Zygote", "FiniteDifferences", "ChainRulesTestUtils", "MLDatasets"]
+test = ["Test", "Adapt", "InlineStrings", "Zygote", "FiniteDifferences", 
+        "ChainRulesTestUtils", "MLDatasets"]

src/GNNGraphs/utils.jl

@@ -18,6 +18,9 @@ cat_features(x1::AbstractArray, x2::AbstractArray) = cat(x1, x2, dims=ndims(x1))
 cat_features(x1::Union{Number, AbstractVector}, x2::Union{Number, AbstractVector}) = 
     cat(x1, x2, dims=1)
 
+# workaround for issue #98 #104
+cat_features(x1::NamedTuple{(), Tuple{}}, x2::NamedTuple{(), Tuple{}}) = (;)
+
 function cat_features(x1::NamedTuple, x2::NamedTuple)
     sort(collect(keys(x1))) == sort(collect(keys(x2))) || @error "cannot concatenate feature data with different keys"
 

test/runtests.jl

@@ -12,6 +12,8 @@ using Graphs
 using Zygote
 using Test
 using MLDatasets
+using InlineStrings  # not used but with the import we test #98 and #104
+
 CUDA.allowscalar(false)
 
 const ACUMatrix{T} = Union{CuMatrix{T}, CUDA.CUSPARSE.CuSparseMatrix{T}}